—This paper presents a methodology to evaluate and optimize the robustness of an embedded system in terms of invariability in case of design revisions. Early decisions in embedde...
In this paper, we present a novel out-of-core technique for the interactive computation of isosurfaces from volume data. Our algorithm minimizes the main memory and disk space req...
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
Just as some functions have uniform behavior over distinct types, other functions have uniform behavior over distinct arities. These variable-arity functions are widely used in scr...
T. Stephen Strickland, Sam Tobin-Hochstadt, Matthi...